数据分析师 | 预测分析决策管理

KEY RESPONSIBILITIES:

• Use appropriate statistical techniques to develop appropriate analytic solutions for informing customer acquisition and customer retention strategies

• Develop appropriate methodology for analyzing and interpreting results from product features A/B testing

• Work on multiple analytic projects such as user segmentations, user engagement to purchase funnel analysis, user life time value analysis

• Provide data, insights and reporting support to various teams

• Drive the collection of new data and the refinement of existing data sources

• Prepare data for statistical analysis and machine learning algorithms

• Maintain and advance analytic database. Conduct periodic data QA

• Working with technical and non-technical customers to design experiments and communicate statistical results

• Leading training and informational sessions on statistics

• Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business

TO QUALIFY:

• Master’s Degree or PhD in a relevant technical field such as Statistics, Math and Computer Science, Mathematics, Economics and Analytics with 7+ years’ experience in a relevant Data Scientist role post-graduation

• Extensive experience solving business problems using quantitative approaches

• Comfort with extracting, manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources

• Strong passion for data driven research for answering hard questions with data

• Early adopters of new tools, technologies, etc.

• Decent understanding of business

• Structured problem-solving skills to translate problems into solutions

• Flexible analytic approach that allows for results at varying levels of precision

• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner

• Familiarity with relational databases and intermediate+ level knowledge of SQL

• Expert knowledge of R; Experience with other analytic tools such as Looker – a strong plus

• Experience working with large data sets, familiarity/experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, etc.)

• Problem-solving and analytical abilities

• Proficiency in any of the statistical software such as R, S-plus, SAS, STATA, python programming etc.

• Good verbal and written communication skills and an ability to work in a team environment

• A solid grounding in applied statistics including expertise in at least one of the following is a must:
• Reliability models

• Markov Models

• Stochastic models

• Bayesian modeling

• Classification models

• Cluster analysis

• Neural network

• Non-parametric methods

• Time series analysis

• Forecasting

• Multivariate statistics

• Experience in building and deploying business relevant analytics assets

• Experience in real time analytics asset development & deployment

• Experience in Applied Machine learning is an added advantage

• Experience in any of the domains:
• Retail

• Consumer Products Marketing

• Network

• Supply Chain

• F&A

• Procurement

• Life Science

• eCommerce

• Banking Finance

• Health Care

• Human Resources

• Digital Marketing

Originally posted on Himalayas